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Data Modeler
Ness Digital EngineeringUnited States, United Statesfull_timeVerifiedPosted 29 Sept 2025
💰 $150,000/yr($130,000/yr – $150,000/yr)
About the role
Ness is a full lifecycle digital engineering firm offering digital advisory through scaled engineering services. Combining our core competence in engineering with the latest in digital strategy and technology, we seamlessly manage Digital Transformation journeys from strategy through execution to help businesses thrive in the digital economy. As your tech partner, we help engineer your company’s future with cloud and data. For more information, visit www.ness.com We are problem-solvers, architects, strategists, implementors, and lifelong learners. We collaborate with each other and with our clients to help them meet their short- and long-term technology goals. Our culture is open, transparent, challenging, and fun. We hire smart, self-starters who thrive in an open-ended environment to figure out what needs to be done and take ownership in delivering quality results Data Modeler (Finance & Capital Markets)Chicago, IL (2-3 days onsite a week) Position Overview:We are looking for a Data Modeler with strong expertise in designing, optimizing, and maintaining conceptual, logical, and physical data models for financial data. The candidate will work closely with data architects, engineers, and business stakeholders to ensure data integrity, performance, and alignment with domain-specific needs in Capital Markets. Key Responsibilities:
- Design and maintain conceptual, logical, and physical data models supporting trading, risk, and compliance functions.
- Work with Medallion Architecture (Bronze/Silver/Gold layers) to align data models with cloud lakehouse design.
- Collaborate with Data Architects and Engineers to translate models into efficient schemas for AWS, Spark, Parquet, Iceberg.
- Model time-series, reference data, market data, and transactional flows specific to Finance & Capital Markets.
- Define data standards, naming conventions, and metadata management practices.
- Optimize data models for performance, scalability, and regulatory reporting needs.
- Partner with business stakeholders to capture requirements and ensure semantic consistency across domains.
- Hands-on experience in data modeling tools (Erwin, ER/Studio, PowerDesigner, or similar).
- Strong knowledge of relational, dimensional, and lakehouse modeling techniques.
- Experience with Parquet, Iceberg, and cloud-native data storage formats.
- Strong understanding of Finance & Capital Markets data structures (trades, positions, risk, reference/master data).
- 5–8 years of relevant data modeling experience.
- Exposure to AWS data services, Databricks, Snowflake, DBT.
- Knowledge of data governance, data lineage, and regulatory compliance.
- Familiarity with Agile delivery model and working with Scrum teams.
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